Regression Analysis of Economic Data?

I am doing a regression analysis of the quantity of a certain product sold as a dependent variable against fuel prices, median family income, and loan rate in a series of data spanning 30 years therefore 30 data points. Should loan rate be in percentages or decimal? Do I need to adjust with consumer price index or inflation?

Regression Analysis of Economic Data?

they should be in decimals and no you should not have to adjust for inflation. the regression should take care of all of that for you. If your numbers look wrong then try an adjustment.

Regression Analysis of Economic Data?

to answer your first part of the question %26quot;Should loan rate be in percentages or decimal?%26quot; This should not make a difference since percentages are numbers in decimals. One equals the other in math.

To answer your second question I would adjust with both the consumer price index and the yearly inflation. This would give your analysis a better informed economical view.

Regression Analysis of Economic Data?

Loan rates are recorded in decimals when the number reflects the overall loan rate cost (per k dollar increments) added to the rising I (inflation) (in dollars) number (assumed rising) every year also added to the overall FP and MFI inflation (in dollars) number. Stats... sh*t...

Regression Analysis of Economic Data?

its best to provide nominal and real data together.

Regression Analysis of Economic Data?

Throw all that analysis crap out the window.The world is to dirty to try to make it a controlled environment analysis crap. The only thing that works in business economics is supply and demand. The cheaper you sell a equal or superior product the more your going to sell. The more money your gone to make.

Regression Analysis of Economic Data?

I suppose percentage is ok, but you should harmonize your data : if your price and income data is adjusted (in real terms), then you should use real interest rates (minus inflation).

I suppose it would be better as you'll avoid structural effect in your data.